Apache Airflow vs. Oracle Data Integrator (ODI)

For a quick job scanning of status and deep-diving into job issues, details, and flows, AirFlow does a good job. No fuss, no muss. The low learning curve as the UI is very straightforward, and navigating it will be familiar after spending some time using it. Our requirements are pretty simple. Job scheduler, workflows, and monitoring. The jobs we run are >100, but still is a lot to review and troubleshoot when jobs don't run. So when managing large jobs, AirFlow dated UI can be a bit of a drawback.

Incentivized

I tried various ETL tools and here is [where and] why I recommend Oracle Data Integrator. 1. When you want to process structured data from different databases - Teradata, Exadata, DB2, SQL, Oracle etc. 2. Oracle Data Integrator supports all platforms, hardware, and OS. This is a major advantage compared to other leading tools. 3. The ELT architecture giving a cutting edge performance over leading ETL tools. There is no need to align Oracle Data Integrator between source and target. ODI uses the source and target servers to perform complex transformations. 4. Speeds up the development and maintenance by reducing the code that developers need to write

Incentivized

• Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
• Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
• Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.

Incentivized

• Converts data from various sources into one target format using various business logic rules and integrates with various DBMS types.
• Transformed data from DB2, SQL Server and other Oracle databases into flat files and then used ETL jobs to load into Oracle DB target
• Data Integrator and Goldengate were used together to accomplish the data movement needed for business and data consolidation in live environment. Data Integrator helped with development and in reducing lead time to convert data into target.

Incentivized

• A local "dry run" or IDE plugin that can validate and simulate DAG execution without needing a full environment.
• Better feedback on DAG parse errors in the UI or CLI.
• Navigating large DAGs with hundreds of tasks can be slow and hard to understand visually.

Incentivized

• Oracle support is not the best when needing help with the system
• The documentation is also very poor and takes very long to generate
• Some parts of it are not intuitive to use and get hard to troubleshoot
• Like other Oracle products, you must have very, very thorough knowledge about their systems to understand
• Like all Oracle products, cost is high

Incentivized

It is maturing and over time will have a good pool of resources. Each new version has addressed the issues of the previous ones. Its getting better and bigger.

For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.

Incentivized

Apache Airflow is suited for a much wider set of use cases compared to Databricks. You can run it anywhere, and there is also no vendor lock-in. With Airflow, we can utilize almost any compute engine. Same thing we want to do with Databricks. There might be some level of difficulty based on the support.

Incentivized

Talend Data Integrator has been evaluated during the setup of the architecture for a customer, in comparison to ODI, since it's an open source ETL. But, differently from the meaning of "open source", it has licence costs too that aren't that different from ODI ones. Moreover, the other components of the business intelligence architecture of the customer were Oracle, so we thought that ODI would suit at best with them, more than a different vendor software.

Incentivized

• Most of the ETL processes were automated, cutting down on human labor.
• Apache Airflow's user interface (UI) was very informative and straightforward.
• Since ETL processes were providing data via airflow, we were able to gain a deeper comprehension of the data at hand.

Incentivized

• Oracle Data Integrator helps provide a business with the data it needs to defend the decisions it makes.
• Oracle Data Integrator allows you to analyze data from what can be separate, different, and often outdated data sources. It allows you to make direct comparisons when analyzing data from different pieces of equipment.
• Data from Oracle Data Integrator was used to analyze manufacturing quality and drive down spoilage, saving the company money.

Incentivized